Cotton microbiome profiling and Cotton Leaf Curl Disease (CLCuD) suppression through microbial consortia associated with Gossypium arboreum

The failure of breeding strategies has caused scientists to shift to other means where the new approach involves exploring the microbiome to modulate plant defense mechanisms against Cotton Leaf Curl Disease (CLCuD). The cotton microbiome of CLCuD-resistant varieties may harbor a multitude of bacterial genera that significantly contribute to disease resistance and provide information on metabolic pathways that differ between the susceptible and resistant varieties. The current study explores the microbiome of CLCuD-susceptible Gossypium hirsutum and CLCuD-resistant Gossypium arboreum using 16 S rRNA gene amplification for the leaf endophyte, leaf epiphyte, rhizosphere, and root endophyte of the two cotton species. This revealed that Pseudomonas inhabited the rhizosphere while Bacillus was predominantly found in the phyllosphere of CLCuV-resistant G. arboreum. Using salicylic acid-producing Serratia spp. and Fictibacillus spp. isolated from CLCuD-resistant G. arboreum, and guided by our analyses, we have successfully suppressed CLCuD in the susceptible G. hirsutum through pot assays. The applied strains exhibited less than 10% CLCuD incidence as compared to control group where it was 40% at 40 days post viral inoculation. Through detailed analytics, we have successfully demonstrated that the applied microbes serve as a biocontrol agent to suppress viral disease in Cotton.


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Gossypium arboreum FDH228 Rhizosphere Gossypium arboreum FDH228 Rhizosphere Gossypium arboreum FDH228 Rhizosphere Supplementary Figure 6.CODA LASSO regression for Gossypium hirsutum PFV1 and Gossypium arboreum FDH228 (Leaf epiphyte) for taxonomic abundance at Genus level A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets, with those that are associated with FH228 (Positive), and those that are associated with PFV-1 (Negative); B) Expression levels of microbes selected from the procedure; and C) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure).

Gossypium arboreum FDH228 Leaf epiphyte
Gossypium arboreum FDH228 Leaf epiphyte Supplementary Figure 7. CODA LASSO regression for Gossypium hirsutum PFV1 and Gossypium arboreum FDH228 (Leaf endophyte) for taxonomic abundance at Genus level A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets, with those that are associated with FDH228 (Positive), and those that are associated with PFV-1 (Negative); B) Expression levels of microbes selected from the procedure; and C) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure).

Gossypium arboreum FDH-228 (Root Endophyte) for MetaCyc pathways A)
−coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.
Gossypium arboreum FDH228 Rhizosphere Gossypium arboreum FDH228 Rhizosphere Gossypium arboreum FDH228 Rhizosphere Supplementary Figure 14.CODA LASSO regression for Gossypium hirsutum PFV-2 and Gossypium arboreum FDH-228 (Leaf Endophyte) for MetaCyc pathways A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.

Supplementary Figure 8 .
CODA LASSO regression for Gossypium arboreum FDH-228and Gossypium hirsutum PFV-2 (Rhizosphere) for taxonomic abundance at Genus level A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.

Supplementary Figure 9 .
CODA LASSO regression for Gossypium arboreum FDH-228and Gossypium hirsutum PFV-2 (Leaf Epiphyte) for taxonomic abundance at Genus level A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.

Supplementary Figure 15 .
CODA LASSO regression for Gossypium hirsutum PFV-1 andGossypium hirsutum PFV-2 (Root Endophyte) for MetaCyc pathways A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.

Supplementary Figure 16 .
cycle PWY-5121 superpathway of geranylgeranyl diphosphate biosynthesis II (via MEP)PWY-7196 superpathway of pyrimidine ribonucleosides salvage MET-SAM-PWY superpathway of S-adenosyl-L-methionine biosynthesis PWY-7199 pyrimidine deoxyribonucleosides salvage PWY-6609 adenine and adenosine salvage III PENTOSE-P-PWY pentose phosphate pathway PWY-5347 superpathway of L-methionine biosynthesis (transsulfuration) PWY-7200 superpathway of pyrimidine deoxyribonucleoside salvage PWY-6317 D-galactose degradation I (Leloir pathway) PWY-6353 purine nucleotides degradation II (aerobic) CODA LASSO regression for Gossypium hirsutum PFV-1 and Gossypium hirsutum PFV-2 (Leaf Endophyte) for MetaCyc pathways A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure).

Supplementary Figure 10. CODA LASSO regression for Gossypium arboreum FDH-228 and Gossypium hirsutum PFV-2 (Leaf Endophyte) for taxonomic abundance at Genus level
A)  −coefficients returned from CODA-LASSO procedure as two disjoint sets (those that are positively related, and those that are negatively related with the temperature) B) The density plot returned from the CODA-LASSO segregates the two groups provides a graphical assessment of the classification accuracy (top: true; bottom: predicted from the procedure); C) Expression levels of microbes selected from the procedure.